Building intelligent systems for science and real‑world impact.

I’m a Ph.D.‑trained computational biophysicist/neuroscientist who builds scientific software, biomedical imaging pipelines, and AI systems; from mechanistic neuron/astrocyte modeling to agentic automation (MCP/n8n), MLOps, and analytics.

Focus Scientific computing • Computer vision • LLM/agent workflows • MLOps • Analytics

Experience

Graduate Research Assistant

University of South Florida

Tampa, FL • Jan 2019 — May 2025
  • Conducted PhD research developing computational models of neuron–astrocyte ion dynamics integrating simulations with experimental data.
  • Built DL-SCAN, a deep-learning microscopy pipeline that improved analysis throughput by >50%.
  • Designed automated workflows to process large imaging datasets and extract quantitative cellular metrics.
  • Collaborated with experimental scientists and contributed to peer-reviewed publications and ongoing manuscripts.
  • Translated computational results into biological insights.

Machine Learning Intern

icardio.ai

Los Angeles, CA • Jun 2024 — Aug 2024
  • Evaluated and optimized a PyTorch model for left ventricle segmentation using echocardiography data.
  • Performed validation and error analysis to support integration into a production MLOps pipeline.
  • Collaborated with engineering teams to ensure reliability in clinical workflows.

Junior ML Engineer

Omdena Inc.

Remote • Nov 2023 — Jan 2024
  • Worked with a global team of ~30 collaborators on deep learning projects.
  • Contributed to Alzheimer’s detection achieving ~99% accuracy.
  • Built microorganism detection models achieving ~92% accuracy.
  • Processed ~5,000 imaging samples across the ML pipeline.
  • Delivered milestones within 40–50 days.

Projects

Use the filters to browse quickly.

Publications

DL‑SCAN (Biomolecules 2024)

Deep-Learning-Based Segmentation of Cells and Analysis (DL-SCAN). Biomolecules 2024, 14, 1348.
https://doi.org/10.3390/biom14111348

Baseline Sodium Heterogeneity in Astrocytes (bioRxiv 2025; accepted for publication at Nature Communications)

Local Differences in Baseline Sodium Shape Astrocytic Potassium Uptake by the NKA. bioRxiv.
https://doi.org/10.1101/2025.11.18.687951

Recommendations

"Alok has been consistently demonstrating exceptional skills and producing valuable work addressing significant challenges in biophysics and neuroscience... Alok has particularly strong skills in computer programming, developing, optimizing, and analyzing biophysical simulations, statistical analysis of large datasets, and Machine Learning techniques, all of which demonstrate his value in both academic and industrial settings."

— Prof. Dr. Ghanim Ullah, University of South Florida
View on LinkedIn →

"From the outset, Alok stood out both for his technical expertise and problem-solving mindset... Additionally, Alok played a key role in coordinating with the deployment team, and the model he trained was ultimately the one deployed."

— Dr. Anjana Sengupta, Omdena Inc.
View on LinkedIn →

"I had the pleasure of working with Alok during his internship at iCardio.ai, where he demonstrated exceptional technical capabilities and professional maturity... He incorporated the model into our MLOps development framework and worked to conduct thorough evaluations using our metrics suite, showcasing both his technical depth and attention to detail."

— Dr. Roman Sandler, iCardio.ai
View on LinkedIn →

Contact